1. Field of the Invention
The present invention relates to a electrical control devices and circuits, and particularly to a sliding mode AGC controller and method that provides a chattering reduction feature applied to interconnected automatic generation control (AGC).
2. Description of the Related Art
The Automatic Generation Control (AGC) problem has been one of the most important issues in the operation and design of contemporary electric power systems. This importance is due to the role of the AGC in securing satisfactory operation of power systems and ensuring constancy of speed for induction and synchronous motors, thereby improving the performance of generating units. The purpose of AGC is to track load variation while maintaining system frequency and tie line power interchanges (for interconnected areas) close to specified values. In this way, transient errors in frequency and tie line power should be minimized, and steady error should not appear.
In the last two decades, many techniques were proposed for the supplementary control of AGC systems. Conventionally, PI and PID controllers are used for AGC. However, PI has many drawbacks, some of which are long settling time and relatively large overshoots in the transient frequency deviations. Furthermore, utilization of optimal control theory has already been examined. The controller design is normally based on the parameters of the linear incremental model of the power system, which, in turn, depend on the condition of the power system. Therefore, the linear optimal controller is sensitive to variations in the plant parameters or operating conditions of the power system. Moreover, the linear optimal controller yields unsatisfactory dynamic response in the presence of Generation Rate Constraint. Other techniques used for designing the secondary control loop for the AGC include Neural Network methods, Superconducting Magnetic Energy Storage (SMES) unit applications, and spline techniques.
Furthermore, the application of a sliding mode controller (SMC) to the AGC problem was considered by many authors. SMC possesses some attractive features, including robustness and good transient response. In the literature, a SM controller has been compared with conventional and optimal control methods for two equal-area non-reheat and reheat thermal systems. However, a systematic method for obtaining the switching vector and optimum feedback gain of the SMC has heretofore not been discussed. Pole placement technique has been utilized in designing the SMC for a single area non-reheat AGC system in previous work, in which the feedback gains were selected by trial and error.
In practice, AGC models are nonlinear. Unfortunately, conventional control design methods are not efficient when nonlinearities are introduced to the incremental models of control systems. Thus, other methods should be utilized for the design of the controllers. One of the most reliable techniques is the iterative heuristic optimization algorithms, which can be used to tune the controllers to obtain their optimum settings. Some of the recent attempts that utilized the iterative heuristic algorithms for solving the AGC problems (for linearized models) can be found in previous work.
Genetic Algorithm (GA) approaches have been used to optimize the feedback gains of the SMC applied to a single area non-reheat AGC. In other related work, Particle Swarm Optimization (PSO) was used for the same purpose. In other related work, only the feedback gains were selected optimally. On the other hand, the switching vector was obtained from another design method reported in literature.
Thus, a sliding mode AGC controller and method solving the aforementioned problems is desired.